Wei, Zi-Xiao and Doctor, Faiyaz and Liu, Yan-Xin and Fan, Shou-Zen and Shieh, Jiann-Shing (2020) An Optimized Type-2 Self-Organizing Fuzzy Logic Controller Applied in Anesthesia for Propofol Dosing to Regulate BIS. IEEE Transactions on Fuzzy Systems, 28 (6). pp. 1062-1072. DOI https://doi.org/10.1109/tfuzz.2020.2969384
Wei, Zi-Xiao and Doctor, Faiyaz and Liu, Yan-Xin and Fan, Shou-Zen and Shieh, Jiann-Shing (2020) An Optimized Type-2 Self-Organizing Fuzzy Logic Controller Applied in Anesthesia for Propofol Dosing to Regulate BIS. IEEE Transactions on Fuzzy Systems, 28 (6). pp. 1062-1072. DOI https://doi.org/10.1109/tfuzz.2020.2969384
Wei, Zi-Xiao and Doctor, Faiyaz and Liu, Yan-Xin and Fan, Shou-Zen and Shieh, Jiann-Shing (2020) An Optimized Type-2 Self-Organizing Fuzzy Logic Controller Applied in Anesthesia for Propofol Dosing to Regulate BIS. IEEE Transactions on Fuzzy Systems, 28 (6). pp. 1062-1072. DOI https://doi.org/10.1109/tfuzz.2020.2969384
Abstract
During general anesthesia, anesthesiologists who provide anesthetic dosage traditionally play a fundamental role to regulate Bispectral Index (BIS). However, in this paper, an optimized type-2 Self-Organizing Fuzzy Logic Controller (SOFLC) is designed for Target Controlled Infusion (TCI) pump related to propofol dosing guided by BIS, to realize automatic control of general anesthesia. The type-2 SOFLC combines a type-2 fuzzy logic controller with a self-organizing (SO) mechanism to facilitate online training while able to contend with operational uncertainties. A novel data driven Surrogate Model (SM) and Genetic Programming (GP) based strategy is introduced for optimizing the type-2 SOFLC parameters offline to handle inter-patient variability. A pharmacological model is built for simulation in which different optimization strategies are tested and compared. Simulation results are presented to demonstrate the applicability of our approach and show that the proposed optimization strategy can achieve better control performance in terms of steady state error and robustness.
Item Type: | Article |
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Uncontrolled Keywords: | Anesthesia; Brain modeling; Fuzzy sets; Fuzzy logic; Optimization; Surgery; Computational modeling; genetic programming (GP); surrogate model (SM); type-2 fuzzy controller |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 07 Feb 2020 12:35 |
Last Modified: | 16 May 2024 20:11 |
URI: | http://repository.essex.ac.uk/id/eprint/26661 |
Available files
Filename: IEEE_We_et_al_Final_2.pdf